Gregoire Altan-Bonnet
ImmunoDynamics Group
Programs in Computational Biology & Immunology
Memorial Sloan-Kettering Cancer Center, New York NY
Title: Modeling how immune responses get reliably established despite
unreliable lymphocytes
Abstract: Decision making in the immune system generally implies
large-scale coordination of lymphocytes’ activity over varied
spatio-temporal scales. Our previous work demonstrated how unreliable
the activation of isolated T lymphocytes can be. In that context,
cell-cell communications are critical to proofread the response of
individual T cells. One prominent mechanism to enforce such cellular
communication is via cytokines, i.e. small proteins that lymphocytes can
secrete and respond to. These cytokines have been shown to be critical
to maintain homeostasis, to enforce peripheral tolerance, to coordinate
differentiation at the global level, to match the diversity of potential
pathogenic challenges (viral, bacterial, fungal, etc).
Here we present a quantitative model of interleukin-2 (IL-2)
communication between T cells. We find that the characteristic
accumulation of IL-2 scales with the strength of antigen activation, but
is made independent of T cell precursor frequency via complex feedback
regulation. We also demonstrate quantitatively how competition for IL-2
between effector T cells and regulatory T cells can be a major mechanism
to decide between immune response and tolerance.
We will discuss how computer models (with experimental validation) are
critical to demonstrate how communication via cytokine regulates T cell
activation. Specifically, we will discuss how multi-scale agent-based
approaches (from individual cell to populations) are necessary to probe
the dynamics of the immune system quantitatively.